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A model contains three major categories of elements: Classifiers, events, and behaviors. Each major category models individuals
in an incarnation of the system being modeled. A classifier describes a set of objects; an object is an individual thing with
a state and relationships to other objects. An event describes a set of possible occurrences; an occurrence is something that
happens that has some consequence within the system. A behavior describes a set of possible executions; an execution is the
performance of an algorithm according to a set of rules. Models do not contain objects, occurrences, and executions, because
those things are the subject of models, not their content. Classes, events, and behaviors model sets of objects, occurrences,
and executions with similar properties. Value specifications, occurrence specifications, and execution specifications model
individual objects, occurrences, and executions within a particular context. The distinction between objects and models of
objects, for example, may appear subtle, but it is important. Objects (and occurrences and executions) are the domain of a
model and, as such, are always complete, precise, and concrete. Models of objects (such as value specifications) can be incomplete,
imprecise, and abstract according to their purpose in the model.